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Maximizing the benefits of collaborative learning in the college classroom

Description
This study tested the effects of two kinds of cognitive, domain-based preparation tasks on learning outcomes after engaging in a collaborative activity with a partner. The collaborative learning method of interest was termed "preparing-to-interact," and is supported in theory by the Preparation for Future Learning (PFL) paradigm and the Interactive-Constructive-Active-Passive…

This study tested the effects of two kinds of cognitive, domain-based preparation tasks on learning outcomes after engaging in a collaborative activity with a partner. The collaborative learning method of interest was termed "preparing-to-interact," and is supported in theory by the Preparation for Future Learning (PFL) paradigm and the Interactive-Constructive-Active-Passive (ICAP) framework. The current work combined these two cognitive-based approaches to design collaborative learning activities that can serve as alternatives to existing methods, which carry limitations and challenges. The "preparing-to-interact" method avoids the need for training students in specific collaboration skills or guiding/scripting their dialogic behaviors, while providing the opportunity for students to acquire the necessary prior knowledge for maximizing their discussions towards learning. The study used a 2x2 experimental design, investigating the factors of Preparation (No Prep and Prep) and Type of Activity (Active and Constructive) on deep and shallow learning. The sample was community college students in introductory psychology classes; the domain tested was "memory," in particular, concepts related to the process of remembering/forgetting information. Results showed that Preparation was a significant factor affecting deep learning, while shallow learning was not affected differently by the interventions. Essentially, equalizing time-on-task and content across all conditions, time spent individually preparing by working on the task alone and then discussing the content with a partner produced deeper learning than engaging in the task jointly for the duration of the learning period. Type of Task was not a significant factor in learning outcomes, however, exploratory analyses showed evidence of Constructive-type behaviors leading to deeper learning of the content. Additionally, a novel method of multilevel analysis (MLA) was used to examine the data to account for the dependency between partners within dyads. This work showed that "preparing-to-interact" is a way to maximize the benefits of collaborative learning. When students are first cognitively prepared, they seem to make the most efficient use of discussion towards learning, engage more deeply in the content during learning, leading to deeper knowledge of the content. Additionally, in using MLA to account for subject nonindependency, this work introduces new questions about the validity of statistical analyses for dyadic data.
ContributorsLam, Rachel Jane (Author) / Nakagawa, Kathryn (Thesis advisor) / Green, Samuel (Committee member) / Stamm, Jill (Committee member) / Arizona State University (Publisher)
Created2013
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Playing vocabulary games and learning academic language with gifted elementary students

Description
Learning academic vocabulary is part of the curriculum for elementary students. Many gifted students learn new words easily but do not necessarily feel positive about studying vocabulary at school. They also do not transfer these words to their own writing. This researcher used games in her own fifth-grade classroom to…

Learning academic vocabulary is part of the curriculum for elementary students. Many gifted students learn new words easily but do not necessarily feel positive about studying vocabulary at school. They also do not transfer these words to their own writing. This researcher used games in her own fifth-grade classroom to teach vocabulary and measured the use of these words in the students' writing. This study also examined students' attitudes about learning vocabulary through games. This mixed-methods study used quantitative data to study the students' retention of the vocabulary words, their usage of the words in their writing, and their attitude toward playing games to learn vocabulary. The researcher also used qualitative data to measure the students' attitudes toward learning with games. Three different vocabulary games were used and one editing game was used during this 18-week study. Quantitative data from test scores and questionnaire responses were analyzed comparing pre and post responses. Writing samples and word tallies were collected throughout the study. Students learned the definitions of vocabulary words while playing games and retained the meanings after 18 weeks, achieving a mean score on the posttest of 71%. No significant usage of the relevant words in student writing samples was found. Qualitative data from questionnaires and field notes were coded and analyzed. A significant gain was shown in how students felt about studying vocabulary after playing games. This study showed positive results in all areas measured.
ContributorsRagatz, Carolyn Mae (Author) / Carlson, David L. (Thesis advisor) / Gee, Elisabeth (Committee member) / Stamm, Jill (Committee member) / Cash, Richard (Committee member) / Arizona State University (Publisher)
Created2015
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Association between Student Engagement and Resilience in the Context of COVID-19

Description

During the global COVID-19 pandemic in 2020, many universities shifted their focus to hosting classes and events online for their student population in order to keep them engaged. The present study investigated whether an association exists between student engagement (an individual’s engagement with class and campus) and resilience. A single-shot…

During the global COVID-19 pandemic in 2020, many universities shifted their focus to hosting classes and events online for their student population in order to keep them engaged. The present study investigated whether an association exists between student engagement (an individual’s engagement with class and campus) and resilience. A single-shot survey was administered to 200 participants currently enrolled as undergraduate students at Arizona State University. A multiple regression analysis and Pearson correlations were calculated. A moderate, significant correlation was found between student engagement (total score) and resilience. A significant correlation was found between cognitive engagement (student’s approach and understanding of his learning) and resilience and between valuing and resilience. Contrary to expectations, participation was not associated with resilience. Potential explanations for these results were explored and practical applications for the university were discussed.
ContributorsEmmanuelli, Michelle (Author) / Jimenez Arista, Laura (Thesis director) / Sever, Amy (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Using Logistic Regression to Predict Stock Trends Based on Bag-of-Words Representations of News Article Headlines

Description

We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones…

We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones Industrial Average. The results showed that a tri-gram bag led to a 49% trend accuracy, a 1% increase when compared to the single-gram representation’s accuracy of 48%.
ContributorsBarolli, Adeiron (Author) / Jimenez Arista, Laura (Thesis director) / Wilson, Jeffrey (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05